Improving the Statistical Performance of Oblique Bifactor Measurement and Predictive Models: An Augmentation Approach

IF 2.5 2区心理学 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

Structural Equation Modeling: A Multidisciplinary Journal Pub Date : 2023-10-09 DOI:10.1080/10705511.2023.2222229

Bo Zhang, Jing Luo, Susu Zhang, Tianjun Sun, Don C. Zhang

引用次数: 0

Abstract

Oblique bifactor models, where group factors are allowed to correlate with one another, are commonly used. However, the lack of research on the statistical properties of oblique bifactor models ren...

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提高倾斜双因子测量和预测模型的统计性能:一种增强方法

通常使用的是倾斜双因素模型，其中允许群体因素相互关联。然而，对斜双因子模型的统计特性研究较少。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Structural Equation Modeling: A Multidisciplinary Journal 数学-数学跨学科应用

CiteScore

8.70

自引率

11.70%

发文量

审稿时长

>12 weeks

期刊介绍： Structural Equation Modeling: A Multidisciplinary Journal publishes refereed scholarly work from all academic disciplines interested in structural equation modeling. These disciplines include, but are not limited to, psychology, medicine, sociology, education, political science, economics, management, and business/marketing. Theoretical articles address new developments; applied articles deal with innovative structural equation modeling applications; the Teacher’s Corner provides instructional modules on aspects of structural equation modeling; book and software reviews examine new modeling information and techniques; and advertising alerts readers to new products. Comments on technical or substantive issues addressed in articles or reviews published in the journal are encouraged; comments are reviewed, and authors of the original works are invited to respond.